Search results for: methodological approaches

Authors: Niall J. English, Sylvia Leatham, Maria Isabel Meza Silva, Denis P. Dowling

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The training and education of under- and post-graduate students can be promoted by more active learning especially in engineering, overcoming more passive and vicarious experiences and approaches in their documented effectiveness. However, the possibility of outreach to young pupils and school-children in primary and secondary schools is a lesser explored area in terms of Education and Public Engagement (EPE) efforts – as relates to feedback and influence on shaping 3rd-level engineering training and education. Therefore, the outreach and school-visit agenda constitutes an interesting avenue to observe how active learning, careers stimulus and EPE efforts for young children and teenagers can teach the university sector, to improve future engineering-teaching standards and enhance both quality and capabilities of practice. This intervention involved careers-outreach efforts to lead to statistical determinations of motivations towards engineering, manufacturing and training. The aim was to gauge to what extent this intervention would lead to an increased careers awareness in engineering, using the method of the schools-visits programme as the means for so doing. It was found that this led to an increase in engagement by school pupils with engineering as a career option and a greater awareness of the importance of manufacturing.

Keywords: outreach, education and public engagement, careers, peer interactions

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Authors: Tesfaye Mengistu

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This thesis aims to investigate the effectiveness of Reinforcement Learning (RL) for Autonomous Energy Management solutions. The study explores the potential of Model Free RL approaches, such as Monte Carlo RL and Q-learning, to improve energy management by autonomously adjusting energy management strategies to maximize efficiency. The research investigates the implementation of RL algorithms for optimizing energy consumption in a single-agent environment. The focus is on developing a framework for the implementation of RL algorithms, highlighting the importance of RL for enabling autonomous systems to adapt quickly to changing conditions and make decisions based on previous experiences. Moreover, the paper proposes RL as a novel energy management solution to address nations' CO2 emission goals. Reinforcement learning algorithms are well-suited to solving problems with sequential decision-making patterns and can provide accurate and immediate outputs to ease the planning and decision-making process. This research provides insights into the challenges and opportunities of using RL for energy management solutions and recommends further studies to explore its full potential. In conclusion, this study provides valuable insights into how RL can be used to improve the efficiency of energy management systems and supports the use of RL as a promising approach for developing autonomous energy management solutions in residential buildings.

Keywords: artificial intelligence, reinforcement learning, monte carlo, energy management, CO2 emission

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Authors: Bruno Pinto Vieira, Marco Antonio Calijorne Soares, Armando Sérgio de Aguiar Filho

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Nowadays, a massive amount of information has been produced by different data sources, including mobile devices and transactional systems. In this scenario, concerns arise on how to maintain or establish data quality, which is now treated as a product to be defined, measured, analyzed, and improved to meet consumers' needs, which is the one who uses these data in decision making and companies strategies. Information that reaches low levels of quality can lead to issues that can consume time and money, such as missed business opportunities, inadequate decisions, and bad risk management actions. The step of selecting, identifying, evaluating, and selecting data sources with significant quality according to the need has become a costly task for users since the sources do not provide information about their quality. Traditional data quality control methods are based on user experience or business rules limiting performance and slowing down the process with less than desirable accuracy. Using advanced machine learning algorithms, it is possible to take advantage of computational resources to overcome challenges and add value to companies and users. In this study, machine learning is applied to data quality analysis on different datasets, seeking to compare the performance of the techniques according to the dimensions of quality assessment. As a result, we could create a ranking of approaches used, besides a system that is able to carry out automatically, data quality assessment.

Keywords: machine learning, data quality, quality dimension, quality assessment

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Authors: Juliet Sorensen, Anna Maitland

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Introduction: Characterized by lack of water and sanitation, food insecurity, and low access to hospitals and clinics, informal urban settlements in Lagos, Nigeria have very poor health outcomes. With little education and a general inability to demand basic rights, these communities are often disempowered and isolated from understanding, claiming, or owning their health needs. Utilizing community-based participatory research characterized by interdisciplinary, cross-cultural partnerships, evidence-based assessments, and both primary and secondary source research, a holistic health education and advocacy program was developed in Lagos to address health barriers for targeted communities. This includes a first of its kind guide formulated to teach community-based health educators how to transmit health information to low-literacy Nigerian audiences while supporting behavior change models and social support mechanisms. This paper discusses the interdisciplinary contributions to developing a health education program while also looking at the need for greater beneficiary ownership and implementation of health justice and access. Methods: In March 2016, an interdisciplinary group of medical, legal, and business graduate students and faculty from Northwestern University conduced a Health Needs Assessment (HNA) in Lagos with a partner and a local non-governmental organization. The HNA revealed that members of informal urban communities in Lagos were lacking basic health literacy, but desired to remedy this lacuna. Further, the HNA revealed that even where the government mandates specific services, many vulnerable populations are unable to access these services. The HNA concluded that a program focused on education, advocacy, and organizing around anatomy, maternal and sexual health, infectious disease and malaria, HIV/AIDS, emergency care, and water and sanitation would respond to stated needs while also building capacity in communities to address health barriers. Results: Based on the HNA, including both primary and secondary source research on integrated health education approaches and behavior change models and responsive, adaptive material development, a holistic program was developed for the Lagos partners and first implemented in November 2016. This program trained community-nominated health educators in adult, low-literacy, knowledge exchange approaches, utilizing information identified by communities as a priority. After a second training in March 2017, these educators will teach community-based groups and will support and facilitate behavior change models and peer-support methods around basic issues like hand washing and disease transmission. They will be supported by community paralegals who will help ensure that newly trained community groups can act on education around access, such as receiving free vaccinations, maternal health care, and HIV/AIDS medicines. Materials will continue to be updated as needs and issues arise, with a focus on identifying best practices around health improvements that can be shared across these partner communities. Conclusion: These materials are the first of their kind, and address a void of health information and understanding pervasive in informal-urban Lagos communities. Initial feedback indicates high levels of commitment and interest, as well as investment by communities in these materials, largely because they are responsive, targeted, and build community capacity. This methodology is an important step in dignity-based health justice solutions, albeit in the process of refinement.

Keywords: community health educators, interdisciplinary and cross cultural partnerships, health justice and access, Nigeria

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Authors: Dalia Elleuch

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Narcissistic Personality Disorder (NPD) manifests as a personality disorder marked by inflated self-importance, heightened sensitivity to criticism, a lack of empathy, a preoccupation with appearance over substance, and features such as arrogance, grandiosity, a constant need for admiration, a tendency to exploit others, and an inclination towards demanding special treatment due to a sense of excessive entitlement (APA, 2013). This interdisciplinary study delves into NPD through the systematic synthesis of psycholinguistic analysis and neuroscientific correlates. The cognitive and emotional dimensions of NPD reveal linguistic patterns, including grandiosity, entitlement, and manipulative communication. Neuroscientific investigations reveal structural brain differences and alterations in functional connectivity, further explaining the neural underpinnings of social cognition deficits observed in individuals with NPD. Genetic predispositions and neurotransmitter imbalances add a layer of complexity to the understanding of NPD. The necessity for linguistic intervention in diagnosing and treating Narcissistic Personality Disorder is underscored by an interdisciplinary study that intricately synthesizes psycholinguistic analysis and neuroscientific correlates, offering a comprehensive understanding of NPD’s cognitive, emotional, and neural dimensions and paving the way for future practical, theoretical, and pedagogical approaches to address the complexities of this personality disorder.

Keywords: Narcissistic Personality Disorder (NPD), psycholinguistic analysis, neuroscientific correlates, interpersonal dysfunction, cognitive empathy

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Authors: A. Chabert

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The present paper is motivated by the current influence of communicative approaches in language policies around the globe (especially through the Common European Framework of Reference), along with the exponential spread of English as a Lingua Franca worldwide. This study focuses on English language learning and teaching in the last year of primary education in Spain (in the bilingual Valencian region), Norway (in the Trondelag region), and China (in the Hunan region) and proposes a plurilingual communicative approach to ELT in line with ELF awareness and the current retheorisation of ELF within multilingualism (Jenkins, 2018). This study, interdisciplinary in nature, attempts to find a convergence point among English Language Teaching, English as a Lingua Franca, Language Ecology and Multilingualism, breaking with the boundaries that separate languages in language teaching and acknowledging English as international communication, while protecting the mother tongue and language diversity within multilingualism. Our experiment included over 400 students across Spain, Norway, and China, and the outcomes obtained demonstrate that despite the different factors involved in different cultures and contexts, a plurilingual approach to English learning improved English scores by 20% in each of the contexts. Through our study, we reflect on the underestimated value of the mother tongue in ELT, as well as the need for a sustainable ELF perspective in education worldwide.

Keywords: English as a Lingua Franca, English language teaching, language ecology, multilingualism

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Authors: Justin Tang

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Balance tests are frequently used to diagnose concussions on the sidelines of sporting events. Manual scoring, however, is labor intensive and subjective, and many concussions go undetected. This study institutes a novel approach to conducting the Balance Error Scoring System (BESS) more quantitatively using Microsoft’s gaming system Kinect, which uses a contactless sensor and several cameras to receive data and estimate body limb positions. Using a machine learning approach, Visual Gesture Builder, and a deterministic approach, MATLAB, we tested whether the Kinect can differentiate between “correct” and erroneous stances of the BESS. We created the two separate solutions by recording test videos to teach the Kinect correct stances and by developing a code using Java. Twenty-two subjects were asked to perform a series of BESS tests while the Kinect was collecting data. The Kinect recorded the subjects and mapped key joints onto their bodies to obtain angles and measurements that are interpreted by the software. Through VGB and MATLAB, the videos are analyzed to enumerate the number of errors committed during testing. The resulting statistics demonstrate a high correlation between manual scoring and the Kinect approaches, indicating the viability of the use of remote tracking devices in conducting concussion tests.

Keywords: automated, concussion detection, contactless sensors, microsoft kinect

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Authors: Galawezh Obaid Othman

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The present investigation was undertaken to evaluate the germ cell toxicity induced by ciprofloxacin antibiotic and the Protective effect of grape seed oil, Ciproflaxin uses include treatment of genitor-urinary and some reproductive tract bacterial infections. One of the most attractive approaches to disease prevention involves the use of natural antioxidants to protect tissue against toxic injury, the possible protective effect of grape seed oil, against ciprofloxacin induced reproductive toxicity on mouse .the animals were randomly divided into four groups consisting of five mice. Group (1) was orally given distilled water (solvent of the used drugs) and kept as a control. Group (2) was administered 6ml/kg. b.w of grape seed oil orally 15 days .Group (3) was administered 206mg/kg. b.w of ciprofloxacin orally for 15 days.. Last group was treated orally with Grape seed oil (6mg/kg b.w. /day) prior to an orally administered ciprofloxacin (CPX) at a dose of 206 mg⁄kg. b.w. by three hours for fifteen days. Ciproflaxin have ability to induce various types of sperm abnormalities such as (Sperm without head, sperm without tail, defective head spearm,swollen head sperm ), The results explored that Grape seed oil possesses statistically significant (p<0.05) protective potential against Ciproflaxin by decreasing sperm abnormalities frequency in mouse.

Keywords: antimutagen, ciprofloxacin, grape seed oil, germ cell

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Authors: Yoonjung An, Yongtae Park

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Knowledge flows are a critical source of faster technological progress and stouter economic growth. Knowledge flows have been accelerated dramatically with the establishment of a patent system in which each patent is required by law to disclose sufficient technical information for the invention to be recreated. Patent analysis, thus, has been widely used to help investigate technological knowledge flows. However, the existing research is limited in terms of both subject and approach. Particularly, in most of the previous studies, business method (BM) patents were not covered although they are important drivers of knowledge flows as other patents. In addition, these studies usually focus on the static analysis of knowledge flows. Some use approaches that incorporate the time dimension, yet they still fail to trace a true dynamic process of knowledge flows. Therefore, we investigate dynamic patterns of knowledge flows driven by BM patents using a Hidden Markov Model (HMM). An HMM is a popular statistical tool for modeling a wide range of time series data, with no general theoretical limit in regard to statistical pattern classification. Accordingly, it enables characterizing knowledge patterns that may differ by patent, sector, country and so on. We run the model in sets of backward citations and forward citations to compare the patterns of knowledge utilization and knowledge dissemination.

Keywords: business method patents, dynamic pattern, Hidden-Markov Model, knowledge flow

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Authors: Geraldine Molina, Malou Allagnat

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Entry through meteorological and climatic phenomena, technical knowledge and engineering sciences has long been favored by the research and local public action to analyze the urban climate, develop strategies to reduce its changes and adapt their spaces. However, in their daily practices and sensitive experiences, city dwellers are confronted with the climate and constantly deal with its fluctuations. In this way, these actors develop knowledge, skills and tactics to regulate their comfort and adapt to climatic variations. Therefore, the empirical observation and analysis of these living experiences represent major scientific and social challenges. This contribution proposes to question these relationships of the inhabitants to urban climate. It tackles the construction of inhabitants’ climatic experiences to answer a central question: how do city dwellers’ deal with the urban climate and adapt to its different variations? Indeed, the city raises the question of how populations adapt to different spatial and temporal climatic variations. Local impacts of global climate change are combined with the urban heat island phenomenon and other microclimatic effects, as well as seasonal, daytime and night-time fluctuations. To provide answers, the presentation will be focused on the results of a CNRS research project (Géraldine Molina), part of which is linked to the European project Nature For Cities (H2020, Marjorie Musy, Scientific Director). From a theoretical point of view, the contribution is based on a renewed definition of adaptation centered on the capacity of individuals and social groups, a recently opened entry from a theoretical point of view by social scientists. The research adopts a "radical interdisciplinary" approach to shed light on the links between social dynamics of climate (inhabitants’ perceptions, representations and practices) and physical processes that characterize urban climate. To do so, it relied on a methodological combination of different survey techniques borrowed from the social sciences (geography, anthropology, sociology) and linked to the work, methodologies and results of the engineering sciences. From 2016 to 2019, a survey was carried out in two districts of Lyon whose morphological, micro-climatic and social characteristics differ greatly, namely the 6th arrondissement and the Guillotière district. To explore the construction of climate experiences over the long term by putting it into perspective with the life trajectories of individuals, 70 semi-directive interviews were conducted with inhabitants. In order to also punctually survey the climate experiments as they unfold in a given time and moment, observation and measurement campaigns of physical phenomena and questionnaires have been conducted in public spaces by an interdisciplinary research team1. The contribution at the ICUC 2020 will mainly focus on the presentation of the presentation of the qualitative survey conducted thanks to the inhabitants’ interviews.

Keywords: sensitive experiences, ways of life, thermal comfort, radical interdisciplinarity

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Authors: Norazah Mohd Suki, Norbayah Mohd Suki

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This research aims to examine the influence of mediating effect of corporate social responsibility on the relationship between consumer awareness of green marketing and purchase intentions in the retail setting. Data from 200 valid questionnaires was analyzed using the partial least squares (PLS) approach for the analysis of structural equation models with SmartPLS computer program version 2.0 as research data does not necessarily have a multivariate normal distribution and is less sensitive to sample size than other covariance approaches. PLS results revealed that corporate social responsibility partially mediated the link between consumer awareness of green marketing and purchase intentions of the product in the retail setting. Marketing managers should allocate a sufficient portion of their budget to appropriate corporate social responsibility activities by engaging in voluntary programs for positive return on investment leading to increased business profitability and long run business sustainability. The outcomes of the mediating effects of corporate social responsibility add a new impetus to the growing literature and preceding discoveries on consumer green marketing awareness, which is inadequately researched in the Malaysian setting. Direction for future research is also presented.

Keywords: green marketing awareness, social responsibility, partial least squares, purchase intention

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: artificial immune system, breast cancer diagnosis, Euclidean function, Gaussian function

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Authors: Andrey Khalov

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The rapid proliferation of unstructured data in IT infrastructure management demands innovative approaches for extracting actionable knowledge. This paper presents a framework for ontology-based knowledge extraction that combines relational graph neural networks (R-GNN) with large language models (LLMs). The proposed method leverages the DOLCE framework as the foundational ontology, extending it with concepts from ITSMO for domain-specific applications in IT service management and outsourcing. A key component of this research is the use of transformer-based models, such as DeBERTa-v3-large, for automatic entity and relationship extraction from unstructured texts. Furthermore, the paper explores how transfer learning techniques can be applied to fine-tune large language models (LLaMA) for using to generate synthetic datasets to improve precision in BERT-based entity recognition and ontology alignment. The resulting IT Ontology (ITO) serves as a comprehensive knowledge base that integrates domain-specific insights from ITIL processes, enabling more efficient decision-making. Experimental results demonstrate significant improvements in knowledge extraction and relationship mapping, offering a cutting-edge solution for enhancing cognitive computing in IT service environments.

Keywords: ontology mapping, R-GNN, knowledge extraction, large language models, NER, knowlege graph

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Authors: Pietro Mortini, Marco Losa

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Objective: Resection of large lesions growing into the third ventricle remains a demanding surgery, sometimes at risk of severe post-operative complications. Transcallosal and transcortical routes were considered as approaches of choice to access the third ventricle, however neurological consequences like memory loss have been reported. We report clinical results of the previously described combined interhemispheric sub-commissural translaminaterminalis approach (CISTA) for the resection of large lesions located in the third ventricle. Methods: Authors conducted a retrospective analysis on 10 patients, who were operated through the CISTA, for the resection of lesions growing into the third ventricle. Results: Total resection was achieved in all cases. Cognitive worsening occurred only in one case. No perioperative deaths were recorded and, at last follow-up, all patients were alive. One year after surgery 80% of patients had an excellent outcome with a KPS 100 and Glasgow Outcome score (GOS) Conclusion: The CISTA represents a safe and effective alternative to transcallosal and transcortical routes to resect lesions growing into the third ventricle. It allows for a multiangle trajectory to access the third ventricle with a wide working area free from critical neurovascular structures, without any section of the corpus callosum, the anterior commissure and the fornix.

Keywords: craniopharingioma, surgery, sub-commissural translaminaterminalis approach (CISTA),

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Authors: Romy Martinez

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This paper focuses on the use of the indigenous language Guarani in Paraguayan popular song and on some key interpreters born between the 1930s and 1980s. It analyses two representative musical genres of Paraguay, the Polka Paraguaya and Guarania. The lyrics of these genres follow one of four poetic-linguistic forms: to be entirely in Guarani, entirely in Spanish, bilingual (alternating verses in Guarani and Spanish), or in Jopará; the last being a form where words of both languages may be mixed in a single verse. Through these forms, the lyrics alternate and combine the indigenous voice with the one introduced with colonisation, in turn reflecting how Guarani seems to constantly transit, to and from, between a position of disdain and of value within Paraguayan society. Through analysing recordings of Polkas, Paraguayas, and Guaranias, it identifies three styles of singing adopted by female singers who include these genres in their repertoires, namely Paraguayan classical folk, Paraguayan folk, and Paraguayan pop-folk. This analysis is informed by a pilot study which consisted of online interviews with several Paraguayan artists, revealing significant aspects of their backgrounds and musical influences. In addition, it draws on autoethnographic approaches, building on the experience of the music researcher and singer. From a decolonising perspective, the paper brings together the distinctive voices and sounds expressed in popular songs from a marginalised country, language, and gender.

Keywords: female singers, Guarani, Paraguayan song, performance

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Authors: Julia Rey Perez, Victoria Dominguez Ruiz

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The phenomenon of depopulation puts the authorities at risk of abandoning a number of rural-urban areas of significant cultural value, affecting their architecture and intangible cultural heritage. The purpose of this research is to present a methodology created according to the UNESCO Recommendation on the Historic Urban Landscape (HUL), which through the identification of cultural values and attributes, leads to ´Strategic Plans´ build upon the culture and heritage. This methodology is based on the analysis of the town from three perspectives: 1) from the public administration, 2) from the discipline of architecture, and 3) from citizen perception. In order to be able to work on the development of a diagnosis from three very different approaches, collaborative cartographies have been used as working tools. The methodology discussed was applied in Valverde de Burguillos, in Spain, leading to the construction of an inclusive ‘Strategic Plan’ that integrates the management of the town within the overall territorial development plan. The importance of incorporating culture and heritage as a conductor for sustainable urban development through the HUL approach has allowed the local authorities to assume these new tools for heritage conservation, acknowledging community participation as the main element for the ´Strategic Plan” elaboration.

Keywords: rural heritage, citizen participation, inclusiveness, urban governance, UNESCO

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Authors: Ghazi Chabchoub, Mouna Feki, Mohamed Abid, Hammadi Ayadi

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Autoimmune thyroid diseases (AITDs), including Graves’ disease (GD) and Hashimoto’s thyroiditis (HT), are inherited as complex traits. Genetic factors associated with AITDs have been tentatively identified by candidate gene and genome scanning approaches. We analysed three intragenic microsatellite markers in the thyroid hormone receptor associated protein 2 gene (THRAP2), mapped near D12S79 marker, which have a potential role in immune function and inflammation [THRAP2-1(TG)n, THRAP2-2 (AC)n and THRAP2-3 (AC)n]. Our study population concerned 12 patients affected with AITDs belonging to a multiplex Tunisian family with high prevalence of AITDs. Fluorescent genotyping was carried out on ABI 3100 sequencers (Applied Biosystems USA) with the use of GENESCAN for semi-automated fragment sizing and GENOTYPER peak-calling software. Statistical analysis was performed using the non parametric Lod score (NPL) by Merlin software. Merlin outputs non-parametric NPLall (Z) and LOD scores and their corresponding asymptotic P values. The analysis for three intragenic markers in the THRAP2 gene revealed strong evidence for linkage (NPL=3.68, P=0.00012). Our results suggested the possible role of THRAP2 gene in AITDs susceptibility in this family.

Keywords: autoimmunity, autoimmune disease, genetic, linkage analysis

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Authors: Frederik Schulte, Stefan Voß

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The adverse effects of air pollution on public health are an increasingly vital problem in planning for urban regions in many parts of the world. The issue is addressed from various angles and by distinct disciplines in research. Epidemiological studies model the relative increase of numerous diseases in response to an increment of different forms of air pollution. A significant share of air pollution in urban regions is related to transport emissions that are often measured and stored in emission inventories. Though, most approaches in transport planning, engineering, and operational design of transport activities are restricted to general emission limits for specific air pollutants and do not consider more nuanced exposure models. We conduct an extensive literature review on exposure models and emission inventories used to study the health impact of transport emissions. Furthermore, we review methods applied in both domains and use emission inventory data of transportation hubs such as ports, airports, and urban traffic for an in-depth analysis of public health impacts deploying medical exposure models. The results reveal specific urban health risks related to transport emissions that may improve urban planning for environmental health by providing insights in actual health effects instead of only referring to general emission limits.

Keywords: emission inventories, exposure models, transport emissions, urban health

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Authors: Anita Yus

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Several Elementary Schools (SD) ‘favored’ by parents, especially those live in big cities in Indonesia, implicitly demand each child enrolled in the first grade of SD to be able to read, write and calculate. This condition urges the parents to push the teachers in PAUD (Kindergarten) to train their children to read, write, and calculate so they have a set of knowledge. According to Piaget, each child is capable of acquiring knowledge when he is given the opportunity to interact with his environment (things, people, and atmosphere). Teachers can make the interaction occur. There are several learning approaches suitable for the characteristics and needs of child’s growth. This paper talks about a research result conducted to investigate how twelve teachers of early childhood program comprehend the constructivist theory of Piaget, and how they inquire, how the children acquire and construct a number of knowledge through occurred interactions. This is a qualitative research with an observation method followed up by a focus group discussion (FGD). The research result shows that there is a reciprocal interaction between the behaviors of teachers and children affected by the size of the classroom and learning source, teaching experiences, education background, teachers’ attitude and motivation, as well as the way the teachers interpret and support the children’s needs. The teachers involved in this research came up with varied perspective on how knowledge acquired by children at first and how they construct it. This research brings a new perspective in understanding children as scientists.

Keywords: constructivist approach, young children as a scientist, teacher practice, teacher education

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Authors: Saneeya Qureshi

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This paper reports doctoral research into the impact of Special Educational Needs Coordinators (SENCOs) on teachers in England, UK. Since 1994, it has been compulsory for all mainstream schools in the UK to have a SENCO who co-ordinates assessment and provision for supporting pupils with Special Educational Needs (SEN), helping teachers to develop and implement optimal SEN planning and resources. SENCOs’ roles have evolved as various policies continually redefined SEN provision, impacting their positioning within the school hierarchical structure. SENCOs in England are increasingly recognised as key members of school senior management teams. In this paper, It will be argued that despite issues around the transformative ‘professionalisation’ of their role, and subsequent conflict around boundaries and power relations, SENCOs enhance teachers’ abilities in terms of delivering optimal SEN provision. There is a significant international dimension to the issue: a similar role in respect of SEN management already exists in countries such as Ireland, Finland and Singapore, whilst in other countries, such as Italy and India, the introduction of a role similar to that of a SENCO is currently under discussion. The research question addressed is: do SENCOs enhance teachers’ abilities to be effective teachers of children with Special Educational Needs? The theoretical framework of the project is that of interpretivism, as it is acknowledged that there are contexts and realities are social constructions. The study applied a mixed method approach consisting of two phases. The first phase involved a purposive survey (n=42) of 223 primary school SENCOs, which enabled a deeper insight into SENCOs’ perceptions of their roles in relation to teachers. The second phase consisted of semi-structured interviews (n=36) of SENCOs, teachers and head teachers, in addition to school SEN-related documentation scrutiny. ‘Trustworthiness’ was accomplished through data and methodological triangulation, in addition to a rigorous process of coding and thematic analysis. The research was informed by an Ethical Code as per national guidelines. Research findings point to the evolutionary aspect of the SENCO role having engendered a culture of expectations amongst practitioners, as SENCOs transition from being ‘fixers’ to being ‘enablers’ of teachers. Outcomes indicate that SENCOs can empower teaching staff through the dissemination of specialist knowledge. However, there must be resources clearly identified for such dissemination to take place. It is imperative that both SENCOs and teachers alike address the issue of absolution of responsibility that arises when the ownership and accountability for the planning and implementation of SEN provision are not clarified so as to ensure the promotion of a positive school ethos around inclusive practices. Optimal outcomes through effective SEN interventions and teaching practices are positively correlated with the inclusion of teachers in the planning and execution of SEN provisions. An international audience can consider how the key findings are being manifest in a global context, with reference to their own educational settings. Research outcomes can aid the development of specific competencies needed to shape optimal inclusive educational settings in accordance with the official global priorities pertaining to inclusion.

Keywords: inclusion, school professionals, school leadership, special educational needs (SEN), special educational needs coordinators (SENCOs)

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Authors: Enrico Maria la Forgia

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Since the 80ies, in specific situations, France’s Muslims have enacted political actions to reply to attacks on their identity or assimilation attempts, using their religious affiliation as a resource for the organization and expression of collective claims. Indeed, despite Islam's internal sectarian and ethnic differences, religion may be politicized when minorities’ social and cultural rights are under attack. French Civil Society organizations, in this specific case with an Islamic background (ICSO - Islamic Civil Society Organizations), play an essential role in defending Muslims’ social and cultural rights. As a matter of fact, Civil Society organized on an ethnic or religious base is a way to strengthen minoritarian communities and their role as political actors, especially in multicultural contexts. Since the first 1983’s “Marche des Beurs” (slang word referring to French citizens with foreign origins), which involved many Muslims, the development of ICSO contributed to the strenghtening of Islam in France, here meant as a Social Movement aiming to constitute a French version of Islam, defending minorities’ cultural and religious rights, and change the perception of Islam itself in national society. However, since a visible and stigmatized minority, ICSO do not relate only to protests as a strategy to achieve their goals: on several occasions, pressure on authorities through personal networks and connections, or the introduction into public debates of bargaining through the exploitation of national or international crisis, might appear as more successfully - public discourses on minorities and Islam are generally considered favorable conditions to advance requests for cultural legitimation. The proposed abstract, based on a literary review and theoretical/methodological reflection on the state of knowledge on the topic, aims to open a new branch of studies and analysis of Civil Society and Social Movements in Europe, focusing on the French Islamic community as a political actor relating on ICSO to pressure society, local, and national authorities to improve Muslims' rights. The opted methodology relies on a qualitative approach based on ethnography and face-to-face interviews addressing heads and middle-high level activists from ICSO, in an attempt to individuate the strategies enacted by ICSO for mobilizing Muslims and build relations with, on one hand, local and national authorities; into the other, with actors belonging to the Civil Society/political sphere. The theoretical framework, instead, relies on the main Social Movements Theories (resources mobilization, political opportunity structure, and contentious/non-contentious movements), aiming to individuate eventual gaps in the analysis of Islamic Social Movements and Civil Society in minoritarian contexts.

Keywords: Islam, islamophobia, civil society, social movements, sociology, qualitative methodology, Islamic activism in social movement theory, political change, Islam as social movement, religious movements, protest and politics, France, Islamic civil society

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Authors: Qian Liu, Steve Furber

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To explore how the brain may recognize objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor~(DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network~(SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modeled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study's largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognize the postures with an accuracy of around 86.4% -only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much-improved cost to performance trade-off in its approach.

Keywords: spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system

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Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

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The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: environmental internet of things, EIoT, machine learning, anomaly detection, environment monitoring

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Authors: Ikram Kamal, Mohamed Blaghen

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Petroleum hydrocarbons are serious problems and global pollutants in the environment due to their toxicity, carcinogenicity and persistent organic pollutant properties. One of the approaches to enhance biodegradation of petroleum hydrocarbons is to use biosurfactant. Biosurfactants are amphiphilic biomolecules produced as metabolic by-products from microorganisms they received considerable attention in the field of environmental remediation processes such as bioremediation. Biosurfactants have been considered as a desirable alternative to synthetic surfactants in various applications particularly in the environmental field. In comparison with their synthetic counterparts, biosurfactants have been reported to be less toxic, biodegradable and persistent. In this study we have investigated the potential of bacterial strains collected aseptically from the lagoon Marchika (water and soil) in Nador, Morocco; for the production of biosurfactants. This study also aimed to optimize the biosurfactant production process by changing the variables that influence the type and amount of biosurfactant produced by these microorganisms such as: carbon sources and also other physical and chemical parameters such as temperature and pH. Emulsification index, methylene blue test and thin layer chromatography (TLC) revealed the ability of strains used in this study to produce compounds that could emulsify gasoline. In addition, a HPLC/MS was used to separate and identify different biosurfactants purified.

Keywords: petroleum hydrocarbons, biosurfactants, biodegradation, lagoon marchika, emulsification index

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Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

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In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

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Authors: Yasemin Ilkay

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Urban spatial pattern interacts with the minds and bodies of citizens and influences their perception and attitudes, which leads to a two-folded map of the same space: physical and Psychogeographic maps. Psychogeography is a field of inquiry (rooted in literature and fiction) investigating how the environment affects the feelings and behaviors of individuals. This term was posed by Situationist International Movement in the 1950s by Guy Debord; in the course of time, the artistic framework evolved into a political issue, especially with the term Dérive, which indicates ‘deviation’ and ‘resistance’ to the existing spatial reality. The term Dérive appeared on the track of Flânéur after one hundred years; and turned out to be a political tool to transform everyday urban life. The three main concepts of psychogeography [walking, dérive, and palimpsest] construct the epistemological framework for a psychogeographic spatial analysis. Mental representations investigating this framework would provide a designer to capture the invisible layers of the gap between ‘how a space is conceived’ and ‘how the same space is perceived and experienced.’ This gap is a neglected but critical issue to discuss in the planning discipline, and psychogeography provides methodological inputs to cover the interrelation among top-down designs of urban patterning and bottom-up reproductions of ‘the soul’ of urban space at the intersection of geography and psychology. City centers and university campuses exemplify opposite poles of spatial organization and walking practice, which may result in differentiated spatial appropriation forms. There is a traditional city center in Van, located at the core of the city with a dense population and several activities, but not connected to Van Lake, which is the largest lake in the country. On the other hand, the university campus is located at the periphery, and although it has a promenade along the lake’s coast and a regional hospital, it presents a limited walking experience with ambiguous forms of spatial appropriation. The city center draws a vivid urban everyday life; however, the campus presents a relatively natural life far away from the center. This paper aims to reveal the differentiated psychogeographic maps of spatial appropriation at the city center vs. the university campus, which is located at the periphery of the city and along the coast of the largest lake in Turkey. The main question of the paper is, “how do the psychogeographic maps of spatial appropriation differentiate at the city center and university campus in Van within the walking experience with reference to the two-folded map assumption.” The experiential maps of a core group of 15 planning students will be created with the techniques of mental mapping, photographing, and narratives through attentive walks conducted together on selected routes; in addition to these attentive walks, 30 more in-depth interviews will be conducted by the core group. The narrative of psychogeographic mapping of spatial appropriation at the two spatial poles would display the conflicting soul of the city with reference to sub-behavioural regions of walking, differentiated forms of derive and layers of palimpsest.

Keywords: attentive walk, body, cognitive geography, derive, experiential maps, psychogeography, Van, Turkey

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Authors: Berna Kalkan, Kenan Aydin

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Companies give importance customer satisfaction to compete the developing and changing market. This is possible when customer reaches the right product, right quality, place, time and cost. In this regard, the extension of logistics services has played active role on formation and development of the different logistics services concept. The concept of logistics services has played important role involved in the healing of economic indicators today. Companies can use logistics providers, thus have competitive advantage and low cost, reducing time, tobe flexibility. In recent years, Fourth Party Logistics (4PL) has emerged as a new concept that includes relationship between suppliers and firms in outsourcing. 4PL provider is an integrator that offers comprehensive supply chain solutions with the technology, resources and capabilities that it possesses. Also, 4PL has attracted as a popular research topic attention in the recent past. In this paper, logistics outsourcing and 4PL concepts are analyzed and a literature review on 4PL activities is given. Also, the previous studies in literature and the approaches that are used in previous studies in literature is presented by analysing on 4PL activities. In this context, a field study will be applied to 4PL providers and service buyer in Turkey. If necessary, results related to this study will be shared in scientific areas.

Keywords: fourth party logistics, literature review, outsourcing, supply chain management

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Authors: Joseph C. Chen, Venkata Mohan Kudapa

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Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations

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Authors: Mehdi Asgarkhani

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Today, investment on Information Technology (IT) solutions in most organizations is the largest component of capital expenditure. As capital investment on IT continues to grow, IT managers and strategists are expected to develop and put in practice effective decision making models (frameworks) that improve decision-making processes for the use of IT in organizations and optimize the investment on IT solutions. To be exact, there is an expectation that organizations not only maximize the benefits of adopting IT solutions but also avoid the many pitfalls that are associated with rapid introduction of technological change. Different organizations depending on size, complexity of solutions required and processes used for financial management and budgeting may use different techniques for managing strategic investment on IT solutions. Decision making processes for strategic use of IT within organizations are often referred to as IT Governance (or Corporate IT Governance). This paper examines IT governance - as a tool for best practice in decision making about IT strategies. Discussions in this paper represent phase I of a project which was initiated to investigate trends in strategic decision making on IT strategies. Phase I is concerned mainly with review of literature and a number of case studies, establishing that the practice of IT governance, depending on the complexity of IT solutions, organization's size and organization's stage of maturity, varies significantly – from informal approaches to sophisticated formal frameworks.

Keywords: IT governance, corporate governance, IT governance frameworks, IT governance components, aligning IT with business strategies

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Authors: Nivethika Ajeethan, Lord Abbey, Svetlana Yurge

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Riboflavin is a water-soluble vitamin and the direct precursor of the flavin cofactors flavin mononucleotide and flavin adenine dinucleotide. Flavins (FLs) are bioactive molecules that have a beneficial effect on plant growth and development. Sinorhizobium meliloti strain 1021 is an α-proteobacterium that forms agronomically important N₂-fixing symbiosis with Medicago plants and secretes a considerable amount of FLs (FL⁺ strain). This strain was also implicated in plant growth promotion in its association with non-legume host plants. However, the mechanism of this plant growth promotion is not well understood. In this study, we evaluated the growth and development of tomato plants inoculated with S. meliloti 1021 and its mutant (FL⁻ strain) with limited ability to secrete FLs. Our preliminary experiments indicated that inoculation with FL⁺ strain significantly increased seedlings' root and shoot length and surface area compared to those of plants inoculated with FL⁻ strain. For example, the root lengths of 9-day old seedlings inoculated with FL⁺ strain were 35% longer than seedlings inoculated with the mutant. Proteomic approaches combined with the analysis of plant physiological responses such as growth and photosynthetic rate, stomatal conductance, transpiration rate, and chlorophyll content will be used to evaluate the host-plant response to bacteria-derived FLs.

Keywords: flavin, plant growth promotion, riboflavin, Sinorhizobium meliloti

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